Regression model

Divlji bootstrap za regresionu inferencu

Divlji bootstrap je metoda resampliranja za regresione modele sa heteroskedastičnim greškama, koju su uveli Wu (1986) i usavršili Davidson i Flachaire (2008). On konstruiše bootstrap distribuciju skaliranjem svakog reziduala sa slučajnim znakom, tako da standardne greške i intervali poverenja ostaju validni kada varijansa greške nije konstantna ili su podaci grupisani.

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Izvori

  1. Wu, C. F. J. (1986). Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis. Annals of Statistics, 14(4), 1261-1295. DOI: 10.1214/aos/1176350142
  2. Davidson, R., & Flachaire, E. (2008). The Wild Bootstrap, Tamed at Last. Journal of Econometrics, 146(1), 162-169. DOI: 10.1016/j.jeconom.2008.08.003

Kako citirati ovu stranicu

ScholarGate. (2026, June 1). Wild Bootstrap for Regression Inference. ScholarGate. https://scholargate.app/sr/statistics/wild-bootstrap

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Citirana u

ScholarGateWild Bootstrap (Wild Bootstrap for Regression Inference). Preuzeto 2026-06-15 sa https://scholargate.app/sr/statistics/wild-bootstrap · Skup podataka: https://doi.org/10.5281/zenodo.20539026